Forecasting-based data-driven model-free adaptive sliding mode attitude control of combined spacecraft

In this paper, a novel forecasting-based data-driven model-free adaptive sliding mode attitude control (FMFASMC) method is proposed for the postcapture combined spacecraft in the presence of unknown mathematical model and external disturbance. First, a forecasting-based data-driven model-free adaptive controller (FMFAC) is developed to ensure its adaptation to various working conditions by simultaneous adjustment of controller parameters with online and offline input–output measurement data. Then, a sliding-mode-based supplementary controller is introduced to improve the tracking performance of FMFAC in terms of robustness. Compared with existing works, the designed control scheme only utilizes the attitude angle and attitude angular velocity of the combined spacecraft, not requiring corresponding mechanism model, thereby dramatically curtailing the complexity and difficulty of relevant controller design. Finally, simulation comparisons between the FMFASMC, FMFAC, and traditional model-free adaptive control (MFAC) are presented for two groups of illustrative examples. The simulation results verify the effectiveness of the proposed control method.